System and method for integrating flight path and site operating data

ABSTRACT

The present approach relates to the inspection of assets, such as assets having parts that move during operation. As discussed herein, operational data for the asset may be incorporated into planning or adapting the flight plan and/or operational commands may be issued to asset in accordance with the flight plan to facilitate acquisition of the inspection data.

BACKGROUND

The subject matter disclosed herein relates to inspection of an asset,such as a system, device, or facility, using one or more robotic agentssuch as drones or other unmanned vehicles.

Various entities may own or maintain different types of assets as partof their operation. Such assets may include physical or mechanicaldevices, structures, or facilities which may, in some instances, haveelectrical and/or chemical aspects as well. Such assets may be used ormaintained for a variety of purposes and may be characterized as capitalinfrastructure, inventory, or by other nomenclature depending on thecontext. For example, assets may include distributed assets, such as apipeline or an electrical grid as well as individual or discrete assets,such as an airplane, a wind turbine generator, a tower, a vehicle, andso forth. Assets may be subject to various types of defects (e.g.,spontaneous mechanical defects, electrical defects as well as routinewear-and-tear) that may impact their operation. For example, over time,the asset may undergo corrosion or cracking due to weather or mayexhibit deteriorating performance or efficiency due to the wear orfailure of component parts.

Typically, one or more human inspectors may inspect, maintain, andrepair the asset. For example, the inspector may locate corrosion on theasset, may locate and quantitatively or qualitatively assess cracks ordefects on the asset, may assess an asset for the degree ofwear-and-tear observed versus what is expected, and so forth. However,depending on the location, size, and/or complexity of the asset, havingone or more human inspectors performing inspection of the asset may takeaway time for the inspectors to perform other tasks or may otherwise betime consuming and labor intensive, requiring personnel time that mightbe more productively spent elsewhere. Additionally, some inspectiontasks may be dull, dirty, or may be otherwise unsuitable for a human toperform. For instance, some assets may have locations that may not beaccessible to humans due to height, confined spaces, or the like.Further, inspections may be performed at times that are based onschedules resulting in either over-inspection or under-inspection.

Further, some assets may, due to the nature of their operation, bedifficult to inspect or assess while in operation, such as due to movingor inaccessible parts. Thus, an inspection may be either incomplete ormay require that the asset be taken offline, and therefore unproductive,during the inspection process. Such outcomes may be undesirable.Further, due to the uncertain nature of the inspection process, i.e.,current inspection findings may impact subsequent scheduling, it may bedifficult to schedule asset downtime so as to minimize the impact of theinspection process.

BRIEF DESCRIPTION

Certain embodiments commensurate in scope with the originally claimeddisclosure are summarized below. These embodiments are not intended tolimit the scope of the claimed disclosure, but rather these embodimentsare intended only to provide a brief summary of possible forms of thedisclosure. Indeed, embodiments may encompass a variety of forms thatmay be similar to or different from the embodiments set forth below.

In one embodiment, an asset inspection system is provided. In accordancewith this embodiment, the asset inspection system includes: an assetcontroller configured to monitor one or more parameters associated withone or more assets and to control operation of the one or more assets;one or more drones; and a flight controller configured to communicatewith the one or more drones and the asset controller and to coordinateoperation of the asset with a flight plan followed by the one or moredrones during an inspection.

In a further embodiment, a method for initiating a drone-basedinspection is provided. In accordance with this method, a command toinitiate an inspection is received. One or both of current environmentaldata or current operational data for one or more assets to be inspectedis acquired. An inspection order is calculated based on one or both ofthe current environmental data or current operational data for the oneor more assets and based on location data for the one or more assets.Based on the inspection order, a flight plan is generated for one ormore drones. The drones are operated in accordance with the flight planto inspect the one or more assets.

In an additional embodiment, a method for inspecting an asset isprovided. In accordance with this method, a first operational command toadjust operation of an asset is sent as one or more drones approach theasset to perform an inspection. A confirmation is received that theoperational command has been performed by the asset. The one or moredrones are instructed to execute a flight plan with respect the assetand to collect inspection data when executing the flight plan. Uponcompletion of the flight plan, A second operational command is sent toreturn the asset to normal operation.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features, aspects, and advantages of the presentinvention will become better understood when the following detaileddescription is read with reference to the accompanying drawings in whichlike characters represent like parts throughout the drawings, wherein:

FIG. 1 shows a wind turbine system configured to convert wind energyinto electrical energy in accordance with aspects of the presentdisclosure;

FIG. 2 is a block diagram of an embodiment of wind power system sitehaving use of a drone-based inspection system, in accordance withaspects of the present disclosure;

FIG. 3 depicts a process flow of an inspection initiation flow, inaccordance with aspects of the present disclosure;

FIG. 4 depicts a process flow of a wind turbine generator inspectioninitiation flow, in accordance with aspects of the present disclosure;

FIG. 5 depicts a process flow of an inspection flow, in accordance withaspects of the present disclosure; and

FIG. 6 depicts a process flow of a wind turbine generator inspectionflow, in accordance with aspects of the present disclosure.

DETAILED DESCRIPTION

One or more specific embodiments will be described below. In an effortto provide a concise description of these embodiments, all features ofan actual implementation may not be described in the specification. Itshould be appreciated that in the development of any such actualimplementation, as in any engineering or design project, numerousimplementation-specific decisions must be made to achieve thedevelopers' specific goals, such as compliance with system-related andbusiness-related constraints, which may vary from one implementation toanother. Moreover, it should be appreciated that such a developmenteffort might be complex and time consuming, but would nevertheless be aroutine undertaking of design, fabrication, and manufacture for those ofordinary skill having the benefit of this disclosure.

When introducing elements of various embodiments of the presentinvention, the articles “a,” “an,” “the,” and “said” are intended tomean that there are one or more of the elements. The terms “comprising,”“including,” and “having” are intended to be inclusive and mean thatthere may be additional elements other than the listed elements.Furthermore, any numerical examples in the following discussion areintended to be non-limiting, and thus additional numerical values,ranges, and percentages are within the scope of the disclosedembodiments.

As discussed herein, the present approach relates to the inspection ofone or more assets, such as power generation assets, transportationassets, mining or underground pumping assets, manufacture orconstruction assets and so forth, using unmanned or robotic devices,such as unmanned aerial vehicles (UAVs), unmanned submersible vehicles(USVs), or other autonomously moving vehicles that may be characterizedas drones or robots. For simplicity, the term “drone” is used herein,though it should be appreciated that this terminology is intended toencompass all variations, of UAVs, USVs, robotic devices, and so forththat are capable of programmable movement with no or limited humanoversight. Such programmable movement can be based on either locallygenerated path waypoints or guidance or path guidance and waypointsgenerated by a remote system and communicated to the drone. Thus, asused herein, such devices move during an operational phase or periodentirely or primarily without direct human intervention or controland/or with limited human intervention or oversight. In accordance withpresent approaches, such devices may be operated to move along a flightplan, along which the devices acquire inspection data, such as video orstill image data, LIDAR data, or other data that can be acquired bysensors or cameras that can be affixed to a device moving along theflight plan.

Though the phrase “flight plan” is used generally herein, it should beappreciated that this phrase does not necessitate aerial movement, butinstead relates to any one-dimensional (1D) (such as along a track),two-dimensional (2D) (such as along a defined or undefined planarroute), or three-dimensional (3D) (such as movement in the air, underwater, or on a structure in where depth or altitude is alsotraversable), or four-dimensional (4D) (such as where there are definedtemporal aspects) path or route along which a drone moves as part of aninspection plan. Thus, a “flight plan” as used herein may becharacterized as any 1D, 2D, 3D, or 4D route or path along which devicesuch as a drone or robot is moved to perform a sensor-based inspectionof an asset. Such a path may be adaptive, as discussed herein, and mayconsist of one or more waypoints along which the drone proceeds in anordered fashion, with the sequence and location of the waypointsdefining the path or route. It should be appreciated that such a flightplan may also incorporate not only temporal and/or spatial locations,but also orientation and/or alignment instructions for movement alongthe path and/or to exhibit at a given waypoint. Thus, the flight planmay also specify parameters such as roll, pitch, and yaw for the droneto exhibit at different points along the flight plan as well as two- orthree-dimensional alignment characteristics that may relate to thedirection in which a sensor or camera is pointing at a point along theflight plan. Thus, the flight plan may address not only where or when adrone is with respect to an inspection site but, at a given location orwaypoint, the direction the drone is facing or otherwise oriented withrespect to.

As discussed herein, the present approach facilitates the inspection ofassets that may otherwise be difficult to inspect when operated, such asassets having moving parts which themselves need to be inspected orwhich generate an environment that would otherwise be hostile to theinspection process. As discussed herein, operational data for the assetmay be incorporated into planning or adapting the flight plan and/oroperational commands may be issued to asset in accordance with theflight plan to facilitate acquisition of the needed inspection data.

To facilitate explanation and provide useful real-world context, anexample of a wind farm having multiple wind turbine generators isdiscussed herein. It should be appreciated however that such an exampleis provided merely to facilitate explanation, and the present approachis suitable for use with a wide range of other assets and at variousother types of sites. Thus, the present approach is not intended to belimited to the context of the present examples.

With the preceding in mind, and turning to the figures, FIG. 1 depicts afront view of a wind turbine generator 10 configured to convert windenergy into electrical energy. The wind turbine generator 10 includes atower 12, a nacelle 14 and blades 16. The blades 16 are coupled to agenerator 18 within the nacelle 14 by a hub 20 that rotates with theblades 16. The blades 16 are configured to convert the linear air flowfrom the wind into rotational motion. As the blades 16 rotate, thecoupling between the hub 20 and the generator 18 within the nacelle 14drives components of the generator 18 to rotate, thereby producingelectrical energy. While three blades 16 are included in the depictedwind turbine generator 10, alternative implementations may include moreor fewer blades 16.

The wind turbine generator 10 may also include a controller 26 tocontrol the operation of the wind turbine generator 10. For example, thecontroller 26 may control the rotational speed (rpm) of the wind turbinegenerator 10, the pitch of the blades 16, the yaw of the wind turbinegenerator 10, as well as other parameters of operation. The controller26 may include control circuitry 28, which may include a processor 30and a memory component 32. The processor may be configured to analyzedata, run programs, execute instructions, optimize operating parametersof the wind turbine generator 10, and control the operating parametersof the wind turbine generator 10. The memory component 32 may be anynon-transitory computer readable medium. The memory component may storedata, processor instructions, programs, optimization algorithms, lookuptables, models, and the like, including processor instructions forimplementing the present approaches discussed herein. Though depicted asan aspect of the wind turbine generator 10, as discussed below thecontroller 26 may be implemented at the site level (i.e., a wind farmcontroller) that monitors and controls operation of a multitude of windturbine systems 10 at a given site.

In the depicted example, the controller 26 may include or communicatewith an operator interface 34. The operator interface 34 may include adisplay and/or operator inputs. The operator interface 34 allows thewind turbine generator 10 to communicate with and be controlled by theoperator and the operator to communicate with the wind turbine generator10. Though the various components of the controller 26 are shown withina common unit or housing for purposes of illustration, in someembodiments the various components (e.g., control circuitry 28,processor 30, memory 32, operator interface 34, display 36, operatorinputs 38, communication circuitry 40, etc.) maybe situated in more thanone unit and/or location (i.e., distributed).

The controller 26 may also include communication circuitry 40. In someembodiments, the communication circuitry may facilitate communicationbetween the controller and an operator (e.g. via a smart device) bywired or wireless communication. In some embodiments, the communicationcircuitry 40 may facilitate communication via a wireless or wiredconnection. In some embodiments, a remote control system 46 and/or adatabase 48 (such as a configuration database as discussed below) may bein communication with the controller 26 via a connected network 44. Theremote control system 46 may allow commands to be remotely issued to oneor more wind turbine systems 10 spread across one or more locations. Thenetwork 44 may also provide access to one or more a databases 48containing configuration and/or historical operational data.

In the depicted example a drone 50 is shown as being in the vicinity ofthe wind turbine generator 10, such as to collect inspection data asdiscussed herein.

Turning to FIG. 2, aspects of a system suitable for inspecting one ormore assets, such as a multitude of wind turbine systems 10 provided asa wind farm 80, is described. In this example, the wind turbinegenerators 10 of the wind farm 80 are individually or collectivelycontrolled or in communication with a controller 26, as previouslydescribed in the context of a single wind turbine generator 10.

By way of example, at the local site (i.e., wind farm 80), SCADA(supervisory control and data acquisition) protocols may be executed onthe controller 26 (or as part of other circuit or processorimplementations) as part of the ongoing operation and oversight of thewind farm 80. In such an implementation, the SCADA protocols orroutines, when implemented, may acquire operational data from each ofthe wind turbine generators 10 of the farm 80 and may control operationof the individual wind turbine generators 10, such as by sendingoperation commands or instructions to the respective wind turbinegenerators 10.

To facilitate such operational monitoring and control by the SCADAroutines, some or all of the wind turbine generators 10 may includesensors that may measure environmental conditions and/or weather datarelevant to the wind turbine generator 10 (such as wind speed, winddirection, atmospheric pressure, temperature, humidity, precipitationover a time period, atmospheric conditions, and so forth). The sensorsmay additionally or alternatively measure parameters related to theoperation of the respective wind turbine generator 10, such as bladerevolutions per minute, temperature, vibration, torque, hours used,electrical power production, and so forth.

Thus the SCADA protocols associated with a given wind turbine generatoror farm of wind turbine generators may be configured to determine one ormore of an operating state, environmental or local conditions, and/orcurrent operational parameters or characteristics for a given generator,such as a nacelle yaw, blade angles, operating state, and so forth foreach generator. In addition, the SCADA protocols may be configured togenerate and transmit commands or instructions to the wind turbinegenerators 10 of the associated farm 80. Examples of such commandsinclude, but are not limited to, commands to start and stop blademovement (and corresponding power generation) and/or commands to assumeknown or specified configurations, such as a “rabbit ear” command (inwhich, for a three-blade turbine, one blade is pointed downward and theother two are angled upwards, such as at 30° angles relative to thesurface).

In the depicted example, the controller 26, and possibly any SCADAroutines executing on the controller 26, is in communication with aconfiguration database 84. Such a configuration database 84 may be usedto store and/or manage various configuration data for the wind turbinegenerators 10 of a respective wind farm 80. For example, for each windturbine generator 10, the configuration database may include modeland/or serial numbers for one or more components, blade identifiers ornumbers, color coding or visual markings associated with each blade, andso forth.

FIG. 2 also depicts a flight controller 90 that is responsible forcoordinating operation of one or more drones 50, such as for inspectionof the wind turbine generators 10 of the farm 80. In one embodiment, thedrone(s) 50 have onboard cellular or network connectivity and cancommunicate with the flight controller 90 at least prior to beginning aninspection. In certain implementations the cellular or networkconnectivity of the drone(s) 50 allow communication during aninspection, allowing inspection data to be communicated to the flightcontroller 90 or other components (e.g., inspection data repository 98)and/or allowing the flight controller to communicate changes to theflight plan to a given drone 50.

In the depicted example, the flight controller is depicted as aprocessor-based system having a one or more processors 94 and a memory92. For example, the processor 94 may execute routines stored in thememory 92 (and/or utilize data stored in the memory 92) to generatecommands or flight plans for the drone(s) 50 used in an inspectionprocess. In the depicted example, the flight controller 90 is incommunication with one or both of the wind turbine controller 26 and/orthe configuration database 84 and may use information obtained fromeither source in the control of the drone(s) 50. Conversely, based oninformation or feedback received from the drone(s) 50, the flightcontroller 90 may update or issue instructions to the wind turbinecontroller 26 and/or the configuration database. Thus, the flightcontroller 90 may in certain embodiments be characterized as being aninterface between the drone(s) 50 and the SCADA protocols employed tooperate and monitor the wind turbine generators 10 of the farm 80, aswell as interfacing with the configuration database 84 whereappropriate.

In addition, the flight controller 90 is depicted as in communicationwith an inspection data database 98, such as an image repository. By wayof example, videos, images, LIDAR data, or other relevant sensor orcamera data acquired by the one or more drones 50 during an inspectionmay be uploaded to the inspection data database 98 as acquired or as abatch after an inspection flight plan is completed. The data within theinspection data database may then be reviewed or validated as part ofthe inspection process. In certain implementations, acquired inspectiondata (e.g., sensors readings, video, still images) may be assessed inreal time or near-real-time, in which case the flight controller 90 mayon-the-fly update flight plan of a drone 50 if acquisition of additionalinspection data is warranted (e.g., additional video or images from adifferent range or angle).

Inspection or image data may also include images of the turbine blades16 that include a visual identifier (e.g., an alphanumeric code, two- orthree-dimensional bar code and so forth) that can be used to match andidentify a given blade undergoing inspection. By way of example, in oneembodiment related to turbine blade inspection, which blade of agenerator is being inspected (or has been inspected) is determined usingoptical character recognition (OCR) techniques and/or a combination ofOCR techniques and paint matching or color coding techniques to analyzemarking on the blades, such as near the roots of the blades. Forexample, using these techniques, blades may be matched using imagesacquired during an inspection compared to a stored repository ofpreviously captured images. In this manner, during an inspection, adrone may be able to infer which blade of a wind turbine generator iswhich.

In the depicted example, the turbine controller 26, flight controller90, configuration database 84, and inspection database 98 are depictedas separate and discrete entities. However, it should be appreciatedthat, depending on the implementation, certain of these aspects may beprovided as different functions or functionalities implemented by asingle or common processor-based system. Conversely, the depictedfunctionalities may be implemented in a distributed or dispersed manner,with certain aspects being local to the wind farm 80 (such as the SCADAor wind turbine controller 26) and other remote from the wind farm 80(such as the inspection database 98. In such distributedimplementations, the depicted aspects may still be communicativelylinked, such as over one or more network connections.

Turning to FIG. 3, an example of algorithm steps in the initiation of aninspection operation are depicted. Such steps may be implemented by aprocessor of a system or component discussed herein to begin the stepsof an asset inspection process. In this example, an initial command 120may be received to begin an inspection, such as by a user interactingwith a user interface of the flight controller 90 or turbine controller26 to issue an inspection command.

In the depicted example, in response to the inspection command 120, astep 124 is performed of acquiring environmental and/or operational data126 for the asset or assets to be inspected. Such operating data 126 mayinclude, but is not limited to, current weather or environmentalconditions as well as data related to an operating state for the assetor assets undergoing inspection. In addition, location data 130 (e.g.,latitude and longitude) for the asset or assets may be acquired eitherfrom the same source or from a separate data source.

In certain implementations, operating data 126, including weather orenvironmental data, may be processed or transformed into higher-levelconstructs which may be used in subsequent processes. By way of example,for a given location, such as a wind farm site, environmental data maybe acquired at multiple locations so as to create a map orrepresentation of localized conditions at different locations of thesite. For instance, in the context of a wind farm, anemometers, windvanes, and so forth may be used to acquire localized wind pattern data,which may vary for different locations within the wind farm. Thislocalized wind pattern data may be represented as a map or other spatialrepresentation which may be used to generate flight plans. Similarly,further processing of the localized environment data based on knowledgeof the drones to be employed in an inspection may allow generation ofcertain types of maps or spatial representations, such as a yaw offsetmap, that may be useful in flight planning, as discussed in greaterdetail below.

Based on the operating data 126 and locations 130, an inspection orderfor the assets, if more than one is to be inspected, is calculated(block 134). From the inspection order, a flight plan 140 may begenerated. The flight plan, as noted above, may consist of a series ofwaypoints to which the drone or drones 50 travel in a specified orderand/or at specified times. As noted above, generation of the flight planmay take into account localized environmental conditions (e.g., windspeed and direction) and or estimated flight characteristics (e.g., yawoffset) in view of the localized environmental conditions and dronecharacteristics.

At certain of the waypoints on the flight plan 140, one or more camerasor sensors may be activated to acquire inspection data. As noted above,the flight plan (or waypoints of the flight plan) might also specifyparticular orientations to be exhibited by the drone(s) at givenwaypoints or while in motion between waypoints. The one or more dronesmay then be operated (block 144) in accordance with the inspectionflight plan.

While FIG. 3 represents a generalized flight plan generation algorithm,FIG. 4 relates steps of an algorithm corresponding to a real-worldimplementation, here the inspection of wind turbine generators. In thisexample, at step 160 the operator commands a drone inspection manager(DIM) computer-implemented routine or program to begin inspecting one ormore wind turbine generators. In response to this instruction, the DIMprogram gathers (step 164) data from the respective wind farm SCADA viaa communication (e.g., network) interface. In one implementation, thedata gathered by the DIM from the SCADA includes, but is not limited to,current operating data, generated power, wind speed, and so forth. Basedon the collected data, the DIM program calculates (step 168) a turbineinspection order based on turbine locations and current operating and/orenvironmental data. By way of example, the turbine inspection order maybe calculated so as to minimize lost production (i.e., powergeneration). Based on the turbine inspection order, at step 172 the DIMprogram may launch one or more drones to inspect the wind generationturbines in the specified order.

Turning to FIG. 5, an example of algorithm steps in the execution of aninspection operation are depicted. Some or all of the steps may beimplemented by a processor of a system or component discussed herein toperform an asset inspection process. In this example, the inspectionprocess involves coordination of the operation of both the asset and thedrone. For example, starting at step 190, as a drone 50 performing aninspection approaches an asset to be inspected, an operational command190 may be issued to the asset to change (block 194) an aspect of itsoperation, such as to stop motion of some component that typically movesduring operation. In the depicted example, the asset, or a controller incommunication with the asset, may issue a confirmation (block 198) thatthe operational command 190 was executed and, in certainimplementations, may provide current operational data 202 for the asset,such as the motion or operational state for various components, theposition or orientation of components that may be mobile, the powerstate of the asset, localized environmental conditions (or flightcharacteristics, such as yaw offset, derived for the localizedenvironmental conditions), and so forth. By way of example, local windspeed and direction, or localized yaw offsets derived for the local windconditions, may be provided at this step.

Based on the operational command 190 being sent and/or on a confirmationor operational data 202 being received, a flight controller 90 incommunication with the drone(s) 50 may make adjustments (block 206) tothe flight plan 140 if justified and convey the modified flight plan 140to the drone 50. Alternatively, in certain embodiments, certain onboardnavigational capability may be provided on the drone 50 itself and, inresponse to receipt of operational data 202, flight plan adjustments maybe made by processing components on the drone itself. By way of example,yaw offset for a given drone, location and sequence of way points, andso forth may be updated based on most recent or real-time wind dataobtained at an inspection site. In one such example, wind data or a yawoffset map derived for such wind data may be monitored in real-time ornear-real-time for changes and/or deviations from expected values and,in response to such changes or deviations (or in expectation of expectedchanges or deviations), a flight plan 140 may be modified onperiodically or on-the-fly.

Based on the flight plan 140, the drone(s) 50 may conduct (block 210) aninspection executing the flight plan 140, i.e., by moving along theflight plan to the various waypoints under the temporal constraintsspecified and operating one or more cameras or sensors based on theflight plan 140. By moving along the flight plan as instructed andoperating its sensors and/or cameras the drone generates a set ofinspection data 214. In one embodiment, the inspection data 214 may beprocessed (block 218) in real time or near-real time, such as todetermine the completeness of the inspection data 214 or to determine ifthe inspection data 214 indicates a potential problem for whichadditional data should be collected. In such scenarios, the flight plan140 may be updated and the inspection resumed to collect whateveradditional inspection data is needed. In other implementations, theinspection data 214 is not downloaded until the drone(s) 50 return totheir base location, at which time the inspection data 214 may beprocessed or analyzed.

In the depicted example, after acquisition of the inspection data 214, arestart command 226 may be sent (block 222) to the asset, instructing itto resume (block 230) operation if some aspect of operation was stoppedor modified for the inspection. In addition, if additional assets are tobe inspected, the drone 50 may proceed (block 234) to the next asset,such as in accordance with the flight plan 140. In such a circumstance,the next asset to be inspected may be issued an operational command 190to stop or modify its operation (block 194) once the drone(s) 50approach the asset, beginning the process shown in FIG. 5 once again.

While FIG. 5 represents a generalized inspection process flow, FIG. 6relates steps of a process flow corresponding to a real-worldimplementation, here the inspection of wind turbine generators. Unlikeprior approaches, the present approach, as described below, integratesthe SCADA operating data for a wind turbine generator to command oradjust operation of the turbines when an inspection drone approaches(e.g., mid-flight) on the basis of drone approach. In this example, atstep 250 drone inspection manager (DIM) routines, such as may beimplemented as part of a flight controller 90, send a stop command to aSCADA in communication with a wind turbine generator 10 to be inspected.In response, at step 254 the SCADA sends a stop command to therespective wind turbine generator 10. Upon receipt of the stop command,the wind turbine generator 10 stops (block 258) rotation of its blades,such as by going into a rabbit ear blade orientation, and sends aconfirmation to the DIM ton confirm a stopped operational state. In thedepicted example, once the wind turbine generator is stopped, the SCADAdetermines the nacelle yaw and blade position of the respective windturbine generator and sends (block 262) this information to the DIM.Based on the operational data received from the SCADA, the DIMcommunicates (block 266) the flight plan to one or more drones 50 whichwill inspect the wind turbine generator. The drone(s) inspect (block270) the wind turbine generator in accordance with the flight plan. Inthis example, the drone(s) 50 send imagery data back to the DIM, such asover an encrypted network connection.

Once the inspection is completed, the drone(s) 50 leave (block 274) thewind turbine generator and the DIM sends a restart command to the SCADA.In response to the restart command, the SCADA instructs the wind turbinegenerator to resume operation (block 278). If additional wind turbinegenerators are to be inspected, the drone(s) 50 move to the nextinspection target (block 282) and the process is repeated. In allgenerators have been inspected, the drone(s) return to base.

Technical effects of the invention include a system that integratesoperating data from a wind turbine (or other asset) to adjust a flightpath or otherwise control a drone conducting an inspection. Based on theproximity of the drone and the status of the inspection, the operationof the asset (e.g., wind turbine) may also be adapted or adjusted,facilitating inspection of those parts of the asset that move duringoperation.

This written description uses examples to disclose the invention,including the best mode, and also to enable any person skilled in theart to practice the invention, including making and using any devices orsystems and performing any incorporated methods. The patentable scope ofthe invention is defined by the claims, and may include other examplesthat occur to those skilled in the art. Such other examples are intendedto be within the scope of the claims if they have structural elementsthat do not differ from the literal language of the claims, or if theyinclude equivalent structural elements with insubstantial differencesfrom the literal languages of the claims.

1. An asset inspection system, comprising: an asset controllerconfigured to monitor one or more parameters associated with one or moreassets and to control operation of the one or more assets; one or moredrones; and a flight controller configured to communicate with the oneor more drones and the asset controller and to coordinate operation ofthe asset with a flight plan followed by the one or more drones duringan inspection.
 2. The asset inspection system of claim 1, wherein theone or more assets comprise one or more of a power generation asset, apipeline, an electrical grid, a vehicle.
 3. The asset inspection systemof claim 1, wherein the one or more assets comprise a wind turbinegenerator.
 4. The asset inspection system of claim 1, furthercomprising: a configuration database configured to store or manageconfiguration data for the one or more assets.
 5. The asset inspectionsystem of claim 1, further comprising: an inspection data repositoryconfigured to receive inspection data generated by the one or moredrones for the one or more assets.
 6. The asset inspection system ofclaim 1, wherein the asset controller is configured to stop and startoperation of the one or more assets in response to instructions receivedfrom the flight controller.
 7. The asset inspection system of claim 1,wherein the flight controller is configured to modify the flight planbased on information received from the asset controller.
 8. The assetinspection system of claim 1, wherein the asset controller is configuredto stop operation of a respective asset based on a first communicationfrom the flight controller that a drone is approaching for an inspectionand to start operation of the asset based on a second communication fromthe flight controller that the drone has completed inspection of therespective asset.
 9. The asset inspection system of claim 1, wherein theasset controller comprises a processor-based system executing one ormore supervisory control and data acquisition (SCADA) protocols.
 10. Amethod for initiating a drone-based inspection, comprising: receiving acommand to initiate an inspection; acquiring one or both of currentenvironmental data or current operational data for one or more assets tobe inspected; calculating an inspection order based on location data forthe one or more assets and on one or both of the current environmentaldata current operational data for the one or more assets; based on theinspection order, generating a flight plan for one or more drones;operating the drones in accordance with the flight plan to inspect theone or more assets.
 11. The method of claim 10, wherein the currentenvironmental data comprises one or more of wind speed, wind direction,atmospheric pressure, temperature, humidity, or precipitation.
 12. Themethod of claim 10, wherein the flight plan is generated based at leastin part on a yaw offset map generated at least in part on the currentenvironmental data.
 13. The method of claim 10, wherein the currentoperational data comprises one or more of blade revolutions per minute,operating temperature, vibration, torque, hours in operation, orelectrical power production.
 14. The method of claim 10, wherein theflight plan comprises one or more waypoints and an associated order inwhich the waypoints are to be visited.
 15. The method of claim 14,wherein the flight plan further comprises a specified orientation forthe respective drone at one or more of the waypoints and an indicationof what sensors or cameras are to be operated at one or more of thewaypoints.
 15. The method of claim 10, wherein calculating theinspection order is based upon minimizing lost production from the oneor more assets.
 17. A method for inspecting an asset, comprising:sending a first operational command to adjust operation of an asset asone or more drones approach the asset to perform an inspection;receiving a confirmation that the operational command has been performedby the asset; instructing the one or more drones to execute a flightplan with respect the asset and to collect inspection data whenexecuting the flight plan; and upon completion of the flight plan,sending a second operational command to return the asset to normaloperation.
 18. The method of claim 17, wherein the first operationalcommand to adjust operation of the asset comprises a stop operationcommand and wherein the second operational command comprises a restartoperation command.
 19. The method of claim 17, further comprising:adjusting the flight plan based on operational data received for theasset.
 20. The method of claim 17, further comprising: adjusting theflight plan based on a yaw offset map generated at least in part usingcurrent environmental data.
 21. The method of claim 17, furthercomprising: transmitting the inspection data to an inspection datarepository during or after the inspection.
 22. The method of claim 17,further comprising: analyzing the flight plan before completion of theflight plan; modifying the flight plan based upon the results ofanalysis to create a modified flight plan; and executing the modifiedflight plan prior to sending the second operation command.